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Postdoctoral In Reinforcement Learning Jobs in Virginia

Postdoctoral Associate Apply now Back to search results Job no: 531898 Work type: Research Faculty ... in learning new techniques; must be able to follow verbal and written instructions; be observant ...

Postdoctoral Associate Apply now Back to search results Job no: 536557 Work type: Research Faculty ... Strong programming proficiency in Python and experience with deep learning frameworks such as ...

Postdoctoral Associate Apply now Back to search results Job no: 536659 Work type: Research Faculty ... in machine learning and molecular simulation Demonstrated a strong publication record Overtime ...

Postdoctoral Associate Apply now Back to search results Job no: 536321 Work type: Research Faculty ... learning. Required Qualifications - Ph.D. in Chemistry, Chemical Engineering, Materials Science ...

Postdoctoral Associate Apply now Back to search results Job no: 536195 Work type: Research Faculty ... The position involves conducting research in federated learning, and network optimization for 6G ...

... reinforcement learning) and neural network architectures like CNNs and RNNs. * AI/ML Frameworks and Libraries: Proficiency is required in tools like TensorFlow, PyTorch, Keras, and scikit-learn.

Autonomy Engineer

Chantilly, VA · Hybrid

$140K - $190K/yr

Experience with reinforcement learning libraries such as RLLib or Gym * Experience with development in Python * Experience with space-based hardware and software, or adjacent aerospace experience

Postdoctoral Associate Apply now Back to search results Job no: 536160 Work type: Research Faculty ... in computational statistics, i.e., unsupervised and supervised ML methods, incl. deep learning.

TS195 Autonomy Engineer

Chantilly, VA · Hybrid

$140K - $190K/yr

Bachelor's degree or higher in Computer/Data Science or related field. * Experience implementing, applying, and analyzing behavior of reinforcement learning algorithms * Experience with reinforcement ...

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Postdoctoral In Reinforcement Learning information

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Reinforcement Learning, and why are they important?

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

What are some common challenges faced by postdoctoral researchers in reinforcement learning, and how can they be addressed?

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is a Postdoctoral Researcher in Reinforcement Learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.
What are popular job titles related to Postdoctoral In Reinforcement Learning jobs in Virginia? For Postdoctoral In Reinforcement Learning jobs in Virginia, the most frequently searched job titles are:
What cities in Virginia are hiring for Postdoctoral In Reinforcement Learning jobs? Cities in Virginia with the most Postdoctoral In Reinforcement Learning job openings:
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Job description

Postdoctoral Associate

Apply now Back to search results Job no: 531898
Work type: Research Faculty
Senior management: College of Veterinary Medicine
Department: Biomedical Science
Location: Blacksburg, Virginia
Categories: Research / Scientific, Veterinary Medicine

Job Description

Looking for an enthusiastic and dedicated postdoctoral associate to join the Kehn-Hall Lab! The Kehn-Hall lab performs research on emerging viruses, including Rift Valley fever virus (RVFV), Venezuelan equine encephalitic virus (VEEV), and eastern equine encephalitis virus (EEEV). The candidate will be responsible for performing cutting edge research to identify FDA approved drugs that can be repurposed for viruses with pandemic potential. This includes working closely with computer scientists to utilize published "omics" datasets and machine learning approaches to identify FDA approved drugs that target key dysregulated pathways/proteins in virally infected cells. The candidate will also assist with the development of liver and/or brain organoid cultures including iPSC-based organoids. Candidate FDA approved drugs will be tested using organoid systems and animal models of infection. The initial focus will be on RVFV, but may be extended to other emerging viruses. The research project is highly collaborative and multidisciplinary involving virologists, computer scientists, and chemical engineers. The candidate, one of six new postdoctoral fellows to be hired within the newly NSF-funded COMPASS Center, will have the opportunity to collaborate with other scientists within the center to tackle complex cross-disciplinary problems in the prevention and control of emerging viruses with pandemic and epidemic potentials.

Required Qualifications

PhD in Microbiology, Molecular Biology, or a closely related field. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
Experience working with RNA viruses
Proficient in cell culture and in vitro viral techniques (infections, plaque assays, generation of virus through reverses genetics systems)
Possess molecular and/or protein biology skills, including experience with RT-qPCR, western blotting, immunoprecipitations, DNA/RNA extractions, plasmid prep, molecular cloning, and transfections.
Capable of receiving Security Risk Assessment (SRA) approval
Experience independently organizing and conducting complex procedures and experiments with minimal supervision
Should be enthusiastic and dedicated, have the ability and interest in learning new techniques; must be able to follow verbal and written instructions; be observant, attentive to detail, organized, efficient, and work well with others

Preferred Qualifications

Experience with organoid systems
Experience working with select agents in Biosafety Level 3 (BSL-3)
Proficient in antiviral activity testing including CC50 and EC50 determinations
Experience with immunohistochemical staining and confocal fluorescent microscopy
Experience working with infectious disease rodent models, including performing inoculations, blood collection, drug treatments, clinical symptom monitoring, euthanasia, gross necropsies, and viral titers analysis of organs.
Knowledge of the regulations, policies, guidelines, and issues surrounding animal technical procedures

 

Appointment Type

Restricted

Salary Information

Commensurate with experience

Review Date

1/15/25

Additional Information

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance.  These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire an accommodation, please contact Chris Whitlock at chrisw15@vt.edu during regular business hours at least 10 business days prior to the event.

Advertised: December 17, 2024
Applications close:

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About Virginia Tech

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Virginia Tech, guided by its motto "Ut Prosim" (That I May Serve), embraces a hands-on, interdisciplinary approach to educate scholars as leaders and problem-solvers. As a comprehensive land-grant institution, it enriches the quality of life in Virginia and worldwide, fostering an inclusive community focused on knowledge, discovery, and creativity. With over 280 majors, the university serves a diverse student body of more than 36,000 across undergraduate, graduate, and professional programs. Virginia Tech's presence extends throughout Virginia, including campuses in Northern Virginia, Roanoke, Newport News, and Richmond, along with multiple Extension offices and research centers. As a prominent global research institution, it conducts over $500 million in research annually.

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Year founded

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